diff --git a/src/implementation.tex b/src/implementation.tex
index ff59628..4f05bf7 100644
--- a/src/implementation.tex
+++ b/src/implementation.tex
@@ -13,4 +13,6 @@ A straight forward machine-learning pipeline was implemented with the help of Py
 
 \begin{lstlisting}
 # todo listing of the sample selection process
-\end{lstlisting}
\ No newline at end of file
+\end{lstlisting}
+
+Moreover, the Dataset was manually imported and preprocessed with random augmentations.
diff --git a/src/main.tex b/src/main.tex
index 0c6090f..fdb9ac8 100644
--- a/src/main.tex
+++ b/src/main.tex
@@ -1,4 +1,4 @@
-\def\ieee{0}
+\def\ieee{1}
 
 \if\ieee1
 \documentclass[sigconf]{acmart}
diff --git a/src/materialandmethods.tex b/src/materialandmethods.tex
index 30ac3ba..3308a10 100644
--- a/src/materialandmethods.tex
+++ b/src/materialandmethods.tex
@@ -3,16 +3,31 @@
 \subsection{Material}\label{subsec:material}
 
 \subsubsection{Dagster}
-Dagster is a data orchestrator for machine learning, analytics, and ETL workflows.
+Dagster is an open-source data orchestrator for machine learning, analytics, and ETL workflows.
 It lets you define pipelines in terms of the data flow between reusable, logical components.
-Dagster is a tool that helps to build scalable and reliable data workflows.
+With Dagster scalable and reliable data workflows can be built.
+
+The most important building blocks in Dagster are Assets, Jobs and Ops.
+Assets are objects in persistent storage which contain a description as code how to update this object.
+Whenever persistent storage is required, eg. storing a model, storing metadata, configurations a asset should be used.
+Assets can be combined to an asset graph to model dependencies of the data flow.
+Jobs are the main triggers of a pipeline and can be triggered by the Web UI, fix schedules or changes of a sensor.
+To perform real tasks in code a Asset consists of an graph of Ops.
+An Op is a function that performs a task and can be used to split the code into reusable components.
+
+Dagster has a well-built web interface to monitor jobs and pipelines.
 
 \subsubsection{Label-Studio}
 \subsubsection{Pytorch}
 \subsubsection{NVTec}
+
+
+
 \subsubsection{Imagenet}
-\subsubsection{Anomalib}
-% todo maybe remove?
+\subsubsection{Muffin vs chihuahua}
+Muffin vs chihuahua is a free dataset available on Kaggle.
+It consists of $\sim$1500 images of muffins and chihuahuas.
+
 
 \subsection{Methods}\label{subsec:methods}